Date & Time:
Wednesday, August 1, 2012; 12:00 PM
In my talk, I will present a self-contained introduction to nonlinear filtering, and describe some recent developments. Specifically, I will introduce the feedback particle filter and show how it admits an innovations error-based feedback control structure. The control is chosen so that the posterior distribution of any particle matches the posterior distribution of the true state given the observations. The subject of my talk is a new formulation of nonlinear filter (for Bayesian inference) that is based on concepts from optimal control and mean-field game theory. Nonlinear filtering is important to many applications in engineering, biology, economics, atmospheric sciences and neuroscience. Several applications will be described to illustrate the theoretical concepts.
This is joint work with Tao Yang and Sean Meyn at the University of Illinois.
Prof. Prashant Mehta
University of Illinois at Urbana-Champaign
Prashant Mehta has received several awards including an Outstanding Achievement Award for his research contributions at UTRC, several Best Paper awards together with his students at Illinois, and numerous teaching and advising honors at Illinois. Prashant Mehta an Associate Professor in the Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign. He received his Ph.D. in Applied Mathematics from Cornell University in 2004. Prior to joining Illinois, he was a Research Engineer at the United Technologies Research Center (UTRC). His research interests are at the intersection of dynamical systems and control theory, including mean-field games, model reduction, and nonlinear control.